Snowflake COF-C02 Practice Exams
Last updated on Oct 22,2026- Exam Code: COF-C02
- Exam Name: SnowPro Core Certification Exam
- Certification Provider: Snowflake
- Latest update: Oct 22,2026
Question #11
A sales table FCT_SALES has 100 million records.
The following Query was executed
SELECT COUNT (1) FROM FCT__SALES;
How did Snowflake fulfill this query?
- A . Query against the result set cache
- B . Query against a virtual warehouse cache
- C . Query against the most-recently created micro-partition
- D . Query against the metadata excite
Correct Answer: D
D
Explanation:
Snowflake is designed to optimize query performance by utilizing metadata for certain types of queries. When executing a COUNT query, Snowflake can often fulfill the request by accessing metadata about the table’s row count, rather than scanning the entire table or micro-partitions. This is particularly efficient for large tables like FCT_SALES with a significant number of records. The metadata layer maintains statistics about the table, including the row count, which enables
Snowflake to quickly return the result of a COUNT query without the need to perform a full scan.
References:
Snowflake Documentation on Metadata Management
SnowPro® Core Certification Study Guide
D
Explanation:
Snowflake is designed to optimize query performance by utilizing metadata for certain types of queries. When executing a COUNT query, Snowflake can often fulfill the request by accessing metadata about the table’s row count, rather than scanning the entire table or micro-partitions. This is particularly efficient for large tables like FCT_SALES with a significant number of records. The metadata layer maintains statistics about the table, including the row count, which enables
Snowflake to quickly return the result of a COUNT query without the need to perform a full scan.
References:
Snowflake Documentation on Metadata Management
SnowPro® Core Certification Study Guide
Question #12
In which use cases does Snowflake apply egress charges?
- A . Data sharing within a specific region
- B . Query result retrieval
- C . Database replication
- D . Loading data into Snowflake
Correct Answer: C
C
Explanation:
Snowflake applies egress charges in the case of database replication when data is transferred out of a Snowflake region to another region or cloud provider. This is because the data transfer incurs costs associated with moving data across different networks. Egress charges are not applied for data sharing within the same region, query result retrieval, or loading data into Snowflake, as these actions do not involve data transfer across regions.
References:
[COF-C02] SnowPro Core Certification Exam Study Guide
Snowflake Documentation on Data Replication and Egress Charges1
C
Explanation:
Snowflake applies egress charges in the case of database replication when data is transferred out of a Snowflake region to another region or cloud provider. This is because the data transfer incurs costs associated with moving data across different networks. Egress charges are not applied for data sharing within the same region, query result retrieval, or loading data into Snowflake, as these actions do not involve data transfer across regions.
References:
[COF-C02] SnowPro Core Certification Exam Study Guide
Snowflake Documentation on Data Replication and Egress Charges1
Question #13
Which feature is integrated to support Multi-Factor Authentication (MFA) at Snowflake?
- A . Authy
- B . Duo Security
- C . One Login
- D . RSA SecurlD Access
Correct Answer: B
B
Explanation:
Snowflake integrates Duo Security to support Multi-Factor Authentication (MFA). This feature provides increased login security for users connecting to Snowflake, and it is managed completely by Snowflake without the need for users to sign up separately with Duo4.
B
Explanation:
Snowflake integrates Duo Security to support Multi-Factor Authentication (MFA). This feature provides increased login security for users connecting to Snowflake, and it is managed completely by Snowflake without the need for users to sign up separately with Duo4.
Question #14
Which of the following practices are recommended when creating a user in Snowflake? (Choose two.)
- A . Configure the user to be initially disabled.
- B . Force an immediate password change.
- C . Set a default role for the user.
- D . Set the number of minutes to unlock to 15 minutes.
- E . Set the user’s access to expire within a specified timeframe.
Correct Answer: B, C
Question #15
The VALIDATE table function has which parameter as an input argument for a Snowflake user?
- A . Last_QUERY_ID
- B . CURRENT_STATEMENT
- C . UUID_STRING
- D . JOB_ID
Correct Answer: C
C
Explanation:
The VALIDATE table function in Snowflake would typically use a unique identifier, such as a UUID_STRING, as an input argument. This function is designed to validate the data within a table against a set of constraints or conditions, often requiring a specific identifier to reference the particular data or job being validated.
References:
There is no direct reference to a VALIDATE table function with these specific parameters in Snowflake documentation. It seems like a theoretical example for understanding function arguments. Snowflake documentation on UDFs and system functions can provide guidance on how to create and use custom functions for similar purposes.
C
Explanation:
The VALIDATE table function in Snowflake would typically use a unique identifier, such as a UUID_STRING, as an input argument. This function is designed to validate the data within a table against a set of constraints or conditions, often requiring a specific identifier to reference the particular data or job being validated.
References:
There is no direct reference to a VALIDATE table function with these specific parameters in Snowflake documentation. It seems like a theoretical example for understanding function arguments. Snowflake documentation on UDFs and system functions can provide guidance on how to create and use custom functions for similar purposes.
Question #16
Which use case does the search optimization service support?
- A . Disjuncts (OR) in join predicates
- B . LIKE/ILIKE/RLIKE join predicates
- C . Join predicates on VARIANT columns
- D . Conjunctions (AND) of multiple equality predicates
Correct Answer: D
D
Explanation:
The search optimization service in Snowflake supports use cases involving conjunctions (AND) of multiple equality predicates. This service enhances the performance of queries that include multiple equality conditions by utilizing search indexes to quickly filter data without scanning entire tables or partitions. It’s particularly beneficial for improving the response times of complex queries that rely on specific data matching across multiple conditions.
References: Snowflake Documentation: Search Optimization Service
D
Explanation:
The search optimization service in Snowflake supports use cases involving conjunctions (AND) of multiple equality predicates. This service enhances the performance of queries that include multiple equality conditions by utilizing search indexes to quickly filter data without scanning entire tables or partitions. It’s particularly beneficial for improving the response times of complex queries that rely on specific data matching across multiple conditions.
References: Snowflake Documentation: Search Optimization Service
Question #17
When using the ALLOW CLIENT_MFA_CACHING parameter, how long is a cached Multi-Factor Authentication (MFA) token valid for?
- A . 1 hour
- B . 2 hours
- C . 4 hours
- D . 8 hours
Correct Answer: C
C
Explanation:
When using the ALLOW_CLIENT_MFA_CACHING parameter, a cached Multi-Factor Authentication (MFA) token is valid for up to 4 hours. This allows for continuous, secure connectivity without users needing to respond to an MFA prompt at the start of each connection attempt to Snowflake within this timeframe2.
C
Explanation:
When using the ALLOW_CLIENT_MFA_CACHING parameter, a cached Multi-Factor Authentication (MFA) token is valid for up to 4 hours. This allows for continuous, secure connectivity without users needing to respond to an MFA prompt at the start of each connection attempt to Snowflake within this timeframe2.
Question #18
What is the relationship between a Query Profile and a virtual warehouse?
- A . A Query Profile can help users right-size virtual warehouses.
- B . A Query Profile defines the hardware specifications of the virtual warehouse.
- C . A Query Profile can help determine the number of virtual warehouses available.
- D . A Query Profile automatically scales the virtual warehouse based on the query complexity.
Correct Answer: A
A
Explanation:
A Query Profile provides detailed execution information for a query, which can be used to analyze the performance and behavior of queries. This information can help users optimize and right-size their virtual warehouses for better efficiency.
References: [COF-C02] SnowPro Core Certification Exam Study Guide
A
Explanation:
A Query Profile provides detailed execution information for a query, which can be used to analyze the performance and behavior of queries. This information can help users optimize and right-size their virtual warehouses for better efficiency.
References: [COF-C02] SnowPro Core Certification Exam Study Guide
Question #19
Which typos of charts does Snowsight support? (Select TWO).
- A . Area charts
- B . Bar charts
- C . Column charts
- D . Radar charts
- E . Scorecards
Correct Answer: A, B
A, B
Explanation:
Snowsight, Snowflake’s user interface for executing and analyzing queries, supports various types of visualizations to help users understand their data better. Among the supported types, area charts and bar charts are two common options. Area charts are useful for representing quantities through the use of filled areas on the graph, often useful for showing volume changes over time. Bar charts, on the other hand, are versatile for comparing different groups or categories of data. Both chart types are integral to data analysis, enabling users to visualize trends, patterns, and differences in their data effectively.
References: Snowflake Documentation on Snowsight Visualizations
A, B
Explanation:
Snowsight, Snowflake’s user interface for executing and analyzing queries, supports various types of visualizations to help users understand their data better. Among the supported types, area charts and bar charts are two common options. Area charts are useful for representing quantities through the use of filled areas on the graph, often useful for showing volume changes over time. Bar charts, on the other hand, are versatile for comparing different groups or categories of data. Both chart types are integral to data analysis, enabling users to visualize trends, patterns, and differences in their data effectively.
References: Snowflake Documentation on Snowsight Visualizations
Question #20
Which data protection feature should only be used when all other data recovery options have been attempted?
- A . Time Travel
- B . Cloning
- C . Replication
- D . Fail-safe
Correct Answer: D
D
Explanation:
The Fail-safe feature in Snowflake is the last-resort data recovery option that should only be used when all other options, such as Time Travel or Cloning, have been exhausted. Fail-safe provides a 7-day recovery period after the Time Travel window has expired but requires Snowflake Support intervention for data recovery. It is intended for disaster recovery and carries additional storage costs.
D
Explanation:
The Fail-safe feature in Snowflake is the last-resort data recovery option that should only be used when all other options, such as Time Travel or Cloning, have been exhausted. Fail-safe provides a 7-day recovery period after the Time Travel window has expired but requires Snowflake Support intervention for data recovery. It is intended for disaster recovery and carries additional storage costs.